datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
forecast-news
Forecast News
Deduplicated daily news corpus used by forecast-sim and future-sim.
Snapshot
31,859,020 articles
3,463 daily partitions
Coverage: 2016-08-26 through 2026-08-31
Snapshot published: 2026-09-18
Stored data size: approximately 158.5 GiB
The Parquet files are the canonical complete representation. The repository also
contains daily JSONL files where available and compact headline JSON files used
by article-browsing workflows.
Layout
Files… See the full description on the dataset page: https://huggingface.co/datasets/shash42/forecast-news.telegram-news-ua-dataset
Aisberg Telegram News UA
A continuously updated, de-identified corpus of Ukrainian Telegram news and the discussion around it, published by the Ukrainian non-profit Aisberg (ГО «АЙЗБЕРГ»). It comes in two layers. The first is the raw monthly stream: every post from a fixed set of public news channels, with its reactions and its comment thread. The second is the analysis behind every report Aisberg publishes: posts from different channels grouped into one event, the manipulation… See the full description on the dataset page: https://huggingface.co/datasets/aisbergpublicorganization/telegram-news-ua-dataset.20_newsgroupsThis is a version of the 20 newsgroups dataset that is provided in Scikit-learn. From the Scikit-learn docs:
The 20 newsgroups dataset comprises around 18000 newsgroups posts on 20 topics split in two subsets: one for training (or development) and the other one for testing (or for performance evaluation). The split between the train and test set is based upon a messages posted before and after a specific date.
We followed the recommended practice to remove headers, signature blocks, and… See the full description on the dataset page: https://huggingface.co/datasets/SetFit/20_newsgroups.LeetCodeDataset
LeetCodeDataset
LeetCodeDataset is a dataset consists of Python leetcode problems that can be used for LLM training and evaluation.
💻 GitHub
📄 LeetCodeDataset: A Temporal Dataset for Robust Evaluation and Efficient Training of Code LLMs
📄 Policy Filtration for RLHF to Mitigate Noise in Reward Models
ag_newsnewswire
Dataset Card for NewsWire
Dataset Summary
NewsWire contains 2.7 million unique public domain U.S. news wire articles, written between 1878 and 1977. Locations in these articles are georeferenced, topics are tagged using customized neural topic classification, named entities are recognized, and individuals are disambiguated to Wikipedia using a novel entity disambiguation model.
Languages
English (en)
Dataset Structure
Each year in the dataset is… See the full description on the dataset page: https://huggingface.co/datasets/dell-research-harvard/newswire.appworld-qwen35-4b-manysource-2k-newprompt-solvability-junhee-epoch8-tmp01-reeval1
appworld-qwen35-4b-manysource-2k-newprompt-solvability-junhee-epoch8-tmp01-reeval1
Portable process-evaluation output. metadata.json is the lightweight source
for aggregate results; the JSONL files are directly loadable; and
artifacts.tar.gz losslessly preserves the original run directory.
Reasoning score: 0.40546875
Action score: 0.475
Valid samples: 320/320
appworld-qwen35-4b-manysource-2k-newprompt-solvability-junhee-epoch8-reeval1
appworld-qwen35-4b-manysource-2k-newprompt-solvability-junhee-epoch8-reeval1
Portable process-evaluation output. metadata.json is the lightweight source
for aggregate results; the JSONL files are directly loadable; and
artifacts.tar.gz losslessly preserves the original run directory.
Reasoning score: 0.4046875
Action score: 0.4703125
Valid samples: 320/320
appworld-qwen35-4b-manysource-2k-newprompt-solvability-junhee-epoch8
appworld-qwen35-4b-manysource-2k-newprompt-solvability-junhee-epoch8
Portable process-evaluation output. metadata.json is the lightweight source
for aggregate results; the JSONL files are directly loadable; and
artifacts.tar.gz losslessly preserves the original run directory.
Reasoning score: 0.39921875
Action score: 0.44375
Valid samples: 320/320
appworld-qwen35-4b-manysource-2k-newprompt-solvability-junhee-epoch8-t01
appworld-qwen35-4b-manysource-2k-newprompt-solvability-junhee-epoch8-t01
Portable process-evaluation output. metadata.json is the lightweight source
for aggregate results; the JSONL files are directly loadable; and
artifacts.tar.gz losslessly preserves the original run directory.
Reasoning score: 0.38359375
Action score: 0.4703125
Valid samples: 320/320
bbc-news
BBC News Topic Dataset
Dataset on BBC News Topic Classification consisting of 2,225 articles published on the BBC News website corresponding during 2004-2005. Each article is labeled under one of 5 categories: business, entertainment, politics, sport or tech.
Original source for this dataset:
Derek Greene, Pádraig Cunningham, “Practical Solutions to the Problem of Diagonal Dominance in Kernel Document Clustering,” in Proc. 23rd International Conference on Machine learning (ICML’06)… See the full description on the dataset page: https://huggingface.co/datasets/SetFit/bbc-news.xlam-function-calling-60k-shareGPTShareGPT converted version of Salesforce/xlam-function-calling-60k
qwen35-4b-filter-s_signal5-200-qwen38-27b-newprompt-4k-epoch4
qwen35-4b-filter-s_signal5-200-qwen38-27b-newprompt-4k-epoch4
Portable process-evaluation output. metadata.json is the lightweight source
for aggregate results; the JSONL files are directly loadable; and
artifacts.tar.gz losslessly preserves the original run directory.
Reasoning score: 0.3890625
Action score: 0.4359375
Valid samples: 320/320
qwen35-4b-filter-solvability-200-qwen38-27b-newprompt-4k-epoch4
qwen35-4b-filter-solvability-200-qwen38-27b-newprompt-4k-epoch4
Portable process-evaluation output. metadata.json is the lightweight source
for aggregate results; the JSONL files are directly loadable; and
artifacts.tar.gz losslessly preserves the original run directory.
Reasoning score: 0.40234375
Action score: 0.421875
Valid samples: 320/320
IndustryCorpus_news[中文主页]
Industry models play a crucial role in driving enterprise intelligence transformation and innovative development. High-quality industry data is key to improving the performance of large models and realizing industry applications. However, datasets currently used for industry model training generally suffer from issues such as insufficient data volume, low quality, and lack of domain expertise.
To address these problems, we constructed and applied 22 industry data processing operators to… See the full description on the dataset page: https://huggingface.co/datasets/BAAI/IndustryCorpus_news.ag_newsAG's News Topic Classification Dataset
Version 3, Updated 09/09/2015
ORIGIN
AG is a collection of more than 1 million news articles. News articles have been gathered from more than 2000 news sources by ComeToMyHead in more than 1 year of activity. ComeToMyHead is an academic news search engine which has been running since July, 2004. The dataset is provided by the academic comunity for research purposes in data mining (clustering, classification, etc), information retrieval (ranking, search… See the full description on the dataset page: https://huggingface.co/datasets/sh0416/ag_news.news-category-datasetDataset from https://www.kaggle.com/datasets/rmisra/news-category-dataset
gdpval_preference_rubricsdaily-bio-newsCSL-News
Summary
This is the dataset proposed in our paper "Uni-Sign: Toward Unified Sign Language Understanding at Scale".
CSL-News is a large-scale Chinese Sign Language dataset designed for developing robust sign language understanding models.
Code: https://github.com/ZechengLi19/Uni-Sign
Download
Please refer to download script to download CSL_News.
You can also download each file by wget, for instance:
wget… See the full description on the dataset page: https://huggingface.co/datasets/ZechengLi19/CSL-News.news-entertainment-datasetGVP_Bot_State_NewIndicVoice-latent-NEWNews_Category_Dataset_v2news-education-datasetnews-politics-datasetnews-tech-datasetnews-finance-datasetnews21-instructionsnetryx-new-york-5km
New York 5km
Pre-computed MegaLoc index for Netryx Drishti geolocation.
Coverage
Center: 40.712800, -74.006000
Radius: 5.0 km
Panoramas: 196,824
Index entries: 787,296
Descriptor model: MegaLoc
Descriptor dim: 1024 (PCA from 8448)
Usage
from netryx_hub import NetryxHub
hub = NetryxHub()
hub.download("new-york-5km", output_dir="./netryx_data/index")
# Now open Netryx and search!
Or download manually and use Import Index in the Netryx GUI.
Details… See the full description on the dataset page: https://huggingface.co/datasets/samsepiol4/netryx-new-york-5km.